1. Field of the Invention
The present invention relates to methods and systems for managing multi-dimensional data and, in particular, to methods and systems for creating, maintaining, and analyzing portfolios of multi-dimensional data, such as project, asset, and product investments, using an object-oriented paradigm.
2. Background Information
Today's companies, institutions, and other organizations are plagued by the vast amount of data which is now stored electronically and often needs to be analyzed by a variety of persons within the organization relative to business or organizational goals. The need to determine efficiently what data is available for analysis and how to analyze disparate data across organizational management boundaries is an ever-increasing problem as the data being tracked increases and as organizations implement more specialized or distributed functions. Managers, executives, employees, and other personnel, each with possibly differing needs for particular content and detail, need to analyze how different changes might effect the projects, products, resources, finances, and assets that each are responsible for. Rapid planning cycles, optimizing the use of critical resources, eliminating low value, non-strategic, redundant, and poorly performing assets and projects, and real time visibility of results are common goals in today's organizations.
The idea of “portfolio management” has evolved within such organizations as a way to emphasize that all assets of an organization, be they financial, human, equipment resources, human resources or other assets, require management and oversight in the same manner as traditional investments such as real property, commercial paper, and equity investments. Managing a group of assets as a portfolio encourages decision makers to view the member investments as a whole but also be able to analyze and scrutinize each discrete investment. Portfolio-based management of IT assets, such as technology investments, has become a popular example of applying portfolio management in a modern day organization. With portfolio-based management, IT information such as inventory lists, spreadsheets, and project management data are managed as assets that need to be analyzed as to how well they are meeting IT and organizational level objectives.
Traditionally, discrete systems have been developed to handle the data management and analysis needs of various entities within an organization. This phenomenon has grown out of the situation that the data for each entity is typically stored in its own subsystem and analysis tools have been developed that are targeted for the specific needs of that entity. Thus, to date, portfolio management systems have been created to separately manage each type of investment. For example, extensive financial management and analysis systems have been developed and used to analyze the financial assets of an organization such as stocks, bonds, and other commercial paper. Classically, the data for these systems is stored in a variety of (typically) relational data base management systems (RDBMS) so that queries can be executed to gain historical insight into the data. “What-if” scenarios are often handled by separate analysis packages that are specific to the type of data being analyzed and the type of analysis conducted. On-line analysis processing packages (OLAP packages) have been developed to support such “what-if” analysis with data that have a large number of axes/variables (often referred to as multi-dimensioned data). For example, an inventory control system of a geographical distributed company may have resource data that can be viewed, analyzed, and sorted by geographic location, region, type of resource, date placed in operation, organization, responsible party, etc. An OLAP package attempts to collect and store such data according to how the data is expected be analyzed so as to optimize analysis efficiency (by reducing search times). In order to analyze the same data according to different views, the system is taken off-line and the data structures are recalculated to prepare for additional analysis. This can be a very time consuming and burdensome process if the data set is very large, as is typical.
Similarly, to handle project management, separate project management and analysis systems have been developed to aid managers and other executives in the project planning and execution lifecycles of projects within an organization. For example, there are systems that offer extensive milestone, critical path, and resource analysis for organization data that can be defined as a project. There exist tools today that allow a group of projects to be viewed as “investments” within a portfolio. These tools provide a way for project managers and other executives within an organization to analyze the costs and benefits of such projects in a similar manner to how financial analysts analyze financial investments.